Lead GTM Enablement & Scale Architect, New Products · Databricks

Sat, 25 Apr 2026 12:05:47 GMT
Engineering

Databricks · United States · $217,800-$299,400 USD · remote

Databricks is entering entirely new markets, e.g. cybersecurity with Lakewatch (an open, agentic SIEM), agentic AI infrastructure, and more categories on the horizon. Each new product means the field needs to learn a new domain, a new competitive landscape, and a new set of customer conversations fast. This is a founding enablement role for Databricks' next wave of products. You won't be inheriting a playbook, you'll be writing a new one, repeatedly, every time Databricks enters a new category. You will own the end-to-end enablement strategy that takes a product from "just announced" to a product every Solutions Architect in the field can confidently qualify, position, demo, and defend in competitive situations. You will be the connective tissue between Product teams building new categories and a global field of SAs, translating capabilities into customer outcomes, and representing the field-readiness voice in Product forums - where the narrative is unclear, where SAs stumble on positioning, where demos need to tighten before a brand-new category reaches the field.

Responsibilities

Own the global GTM and enablement strategy for every new product category Databricks enters - from foundational knowledge through advanced competitive positioning against incumbents

Build and ship enablement at scale using AI: use vibe coding, and AI content pipelines to generate first-draft technical deep dives, competitive talk tracks, hands-on labs, and demo environments - then curate for accuracy and field impact

Design and build demo environments and POC patterns that SAs can fork and customize for customer conversations - you're an architect, not a slide maker

Partner directly with Product and Engineering leadership across new product lines to stay ahead of the roadmap and translate upcoming features into field-ready assets before GA

Establish a tight product feedback loop - systematically capture field friction, lost deals, and SA objections and channel them back to Product with actionable recommendations. You have the standing to tell PMs what's not working and the data to back it up

Design the competitive narrative architecture and build the "why Databricks" story that gives an SA confidence walking into a room with a customer executive.

Create scalable, multi-format enablement: Deep dives, solutions, AI role-plays, hands-on labs, and self-paced learning paths - always with a bias toward assets SAs can use in a customer conversation that same week

Build AI-powered tools that make the field smarter: Glean agents for instant answers, AI role-plays for pitch practice, automated competitive briefs from real-time market signals

Define and track KPIs that measure field readiness, and whether SAs are actually winning more Lakebase deals

Stay a practitioner yourself: spend ~10-15% of your time in customer-facing moments - customer executive briefings, select competitive POCs, because what you build is sharper when you've defended the position in front of a customer executive, not just written it down

Take a step back, think strategically and innovate your approaches to keep up with the fast-paced environment.

What We Look For

8+ years in solutions architecture, technical pre-sales, developer relations, technical product marketing, or technical enablement

You've been the SA in the room: you know what it feels like to run a POC, handle objections live, and defend a technical position against a competitor. That lived experience is what makes your enablement credible

Demonstrated ability to go deep fast in unfamiliar technical domains - the "T-shaped" technologist who can become credible in a new technology one quarter and a new category the next

Builder mentality: you default to building tools, demos, and automations - not decks. You use AI tools as a daily force multiplier, not a novelty

Demonstrated ability to build enablement programs from scratch (0-to-1) - not just iterate on existing content. You see a blank page as an opportunity, not a problem

Strong product instinct: you can look at a feature roadmap for a brand-new category and immediately see how it maps to customer use cases and competitive differentiation

Experience working directly with Product and Engineering teams as a peer, not just a consumer of their content

The backbone to tell Product "the field can't sell this because X" - backed by data and field evidence

Scaling mindset: everything you build needs to work for a global technical field team, not a 20-person workshop. You think about leverage and automation before you think about live delivery

Exceptional communication skills - you can make complex technical concepts accessible to a broad audience, from SAs to C-Suite

Nice to Have

Experience at a high-growth infrastructure company during a major product launch

Background in both pre-sales and post-sales technical roles - you've lived the full customer lifecycle

Hands-on experience with Databricks or competitive platforms

Experience building AI applications on operational databases (RAG patterns, agent architectures, etc.)

You've already used AI to build at scale - automating content creation, building internal tools, or shipping demos faster than anyone thought possible